本文整理汇总了Python中numpy.core.getlimits.finfo方法的典型用法代码示例。如果您正苦于以下问题：Python getlimits.finfo方法的具体用法？Python getlimits.finfo怎么用？Python getlimits.finfo使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类numpy.core.getlimits的用法示例。
在下文中一共展示了getlimits.finfo方法的5个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: _getmaxmin
# 需要导入模块: from numpy.core import getlimits [as 别名]
# 或者: from numpy.core.getlimits import finfo [as 别名]
def _getmaxmin(t):
from numpy.core import getlimits
f = getlimits.finfo(t)
return f.max, f.min 示例2: real_if_close
# 需要导入模块: from numpy.core import getlimits [as 别名]
# 或者: from numpy.core.getlimits import finfo [as 别名]
def real_if_close(a, tol=100):
"""
If complex input returns a real array if complex parts are close to zero.
"Close to zero" is defined as `tol` * (machine epsilon of the type for
`a`).
Parameters
----------
a : array_like
Input array.
tol : float
Tolerance in machine epsilons for the complex part of the elements
in the array.
Returns
-------
out : ndarray
If `a` is real, the type of `a` is used for the output. If `a`
has complex elements, the returned type is float.
See Also
--------
real, imag, angle
Notes
-----
Machine epsilon varies from machine to machine and between data types
but Python floats on most platforms have a machine epsilon equal to
2.2204460492503131e-16. You can use 'np.finfo(float).eps' to print
out the machine epsilon for floats.
Examples
--------
>>> np.finfo(float).eps
2.2204460492503131e-16
>>> np.real_if_close([2.1 + 4e-14j], tol=1000)
array([ 2.1])
>>> np.real_if_close([2.1 + 4e-13j], tol=1000)
array([ 2.1 +4.00000000e-13j])
"""
a = asanyarray(a)
if not issubclass(a.dtype.type, _nx.complexfloating):
return a
if tol > 1:
from numpy.core import getlimits
f = getlimits.finfo(a.dtype.type)
tol = f.eps * tol
if _nx.all(_nx.absolute(a.imag) < tol):
a = a.real
return a 示例3: real_if_close
# 需要导入模块: from numpy.core import getlimits [as 别名]
# 或者: from numpy.core.getlimits import finfo [as 别名]
def real_if_close(a,tol=100):
"""
If complex input returns a real array if complex parts are close to zero.
"Close to zero" is defined as `tol` * (machine epsilon of the type for
`a`).
Parameters
----------
a : array_like
Input array.
tol : float
Tolerance in machine epsilons for the complex part of the elements
in the array.
Returns
-------
out : ndarray
If `a` is real, the type of `a` is used for the output. If `a`
has complex elements, the returned type is float.
See Also
--------
real, imag, angle
Notes
-----
Machine epsilon varies from machine to machine and between data types
but Python floats on most platforms have a machine epsilon equal to
2.2204460492503131e-16. You can use 'np.finfo(float).eps' to print
out the machine epsilon for floats.
Examples
--------
>>> np.finfo(float).eps
2.2204460492503131e-16
>>> np.real_if_close([2.1 + 4e-14j], tol=1000)
array([ 2.1])
>>> np.real_if_close([2.1 + 4e-13j], tol=1000)
array([ 2.1 +4.00000000e-13j])
"""
a = asanyarray(a)
if not issubclass(a.dtype.type, _nx.complexfloating):
return a
if tol > 1:
from numpy.core import getlimits
f = getlimits.finfo(a.dtype.type)
tol = f.eps * tol
if _nx.all(_nx.absolute(a.imag) < tol):
a = a.real
return a 示例4: real_if_close
# 需要导入模块: from numpy.core import getlimits [as 别名]
# 或者: from numpy.core.getlimits import finfo [as 别名]
def real_if_close(a,tol=100):
"""
If complex input returns a real array if complex parts are close to zero.
"Close to zero" is defined as `tol` * (machine epsilon of the type for
`a`).
Parameters
----------
a : array_like
Input array.
tol : float
Tolerance in machine epsilons for the complex part of the elements
in the array.
Returns
-------
out : ndarray
If `a` is real, the type of `a` is used for the output. If `a`
has complex elements, the returned type is float.
See Also
--------
real, imag, angle
Notes
-----
Machine epsilon varies from machine to machine and between data types
but Python floats on most platforms have a machine epsilon equal to
2.2204460492503131e-16. You can use 'np.finfo(np.float).eps' to print
out the machine epsilon for floats.
Examples
--------
>>> np.finfo(np.float).eps
2.2204460492503131e-16
>>> np.real_if_close([2.1 + 4e-14j], tol=1000)
array([ 2.1])
>>> np.real_if_close([2.1 + 4e-13j], tol=1000)
array([ 2.1 +4.00000000e-13j])
"""
a = asanyarray(a)
if not issubclass(a.dtype.type, _nx.complexfloating):
return a
if tol > 1:
from numpy.core import getlimits
f = getlimits.finfo(a.dtype.type)
tol = f.eps * tol
if _nx.all(_nx.absolute(a.imag) < tol):
a = a.real
return a 示例5: real_if_close
# 需要导入模块: from numpy.core import getlimits [as 别名]
# 或者: from numpy.core.getlimits import finfo [as 别名]
def real_if_close(a,tol=100):
"""
If complex input returns a real array if complex parts are close to zero.
"Close to zero" is defined as `tol` * (machine epsilon of the type for
`a`).
Parameters
----------
a : array_like
Input array.
tol : float
Tolerance in machine epsilons for the complex part of the elements
in the array.
Returns
-------
out : ndarray
If `a` is real, the type of `a` is used for the output. If `a`
has complex elements, the returned type is float.
See Also
--------
real, imag, angle
Notes
-----
Machine epsilon varies from machine to machine and between data types
but Python floats on most platforms have a machine epsilon equal to
2.2204460492503131e-16. You can use 'np.finfo(np.float).eps' to print
out the machine epsilon for floats.
Examples
--------
>>> np.finfo(np.float).eps
2.2204460492503131e-16
>>> np.real_if_close([2.1 + 4e-14j], tol=1000)
array([ 2.1])
>>> np.real_if_close([2.1 + 4e-13j], tol=1000)
array([ 2.1 +4.00000000e-13j])
"""
a = asanyarray(a)
if not issubclass(a.dtype.type, _nx.complexfloating):
return a
if tol > 1:
from numpy.core import getlimits
f = getlimits.finfo(a.dtype.type)
tol = f.eps * tol
if _nx.allclose(a.imag, 0, atol=tol):
a = a.real
return a